A residual-convolution-recurrent network with K-margin segment selection and voting achieves 0.8125 F1NAOP on the PhysioNet 2017 atrial fibrillation benchmark.
Comparing feature-based clas- sifiers and convolutional neural networks to detect arrhyth- mia from short segments of ecg
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K-margin-based Residual-Convolution-Recurrent Neural Network for Atrial Fibrillation Detection
A residual-convolution-recurrent network with K-margin segment selection and voting achieves 0.8125 F1NAOP on the PhysioNet 2017 atrial fibrillation benchmark.